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Daniele Ucci
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2020 – today
- 2023
- [j3]Filippo Sobrero, Beatrice Clavarezza, Daniele Ucci
, Federica Bisio:
Towards a Near-Real-Time Protocol Tunneling Detector Based on Machine Learning Techniques. J. Cybersecur. Priv. 3(4): 794-807 (2023) - [c9]Giovanni Graziano, Daniele Ucci
, Federica Bisio, Luca Oneto:
PhishVision: A Deep Learning Based Visual Brand Impersonation Detector for Identifying Phishing Attacks. OL2A (1) 2023: 123-134 - [i5]Filippo Sobrero, Beatrice Clavarezza, Daniele Ucci, Federica Bisio:
Towards a Near-real-time Protocol Tunneling Detector based on Machine Learning Techniques. CoRR abs/2309.12720 (2023) - 2021
- [c8]Daniele Ucci
, Filippo Sobrero, Federica Bisio, Matteo Zorzino:
Near-real-time Anomaly Detection in Encrypted Traffic using Machine Learning Techniques. SSCI 2021: 1-8 - [i4]Nicola Loi, Claudio Borile, Daniele Ucci:
Towards an Automated Pipeline for Detecting and Classifying Malware through Machine Learning. CoRR abs/2106.05625 (2021) - 2020
- [j2]Luca Massarelli
, Leonardo Aniello
, Claudio Ciccotelli, Leonardo Querzoni
, Daniele Ucci, Roberto Baldoni:
AndroDFA: Android Malware Classification Based on Resource Consumption. Inf. 11(6): 326 (2020) - [c7]Daniele Ucci
, Roberto Perdisci
, Jaewoo Lee, Mustaque Ahamad:
Towards a Practical Differentially Private Collaborative Phone Blacklisting System. ACSAC 2020: 100-115 - [i3]Daniele Ucci, Roberto Perdisci, Jaewoo Lee, Mustaque Ahamad:
Building a Collaborative Phone Blacklisting System with Local Differential Privacy. CoRR abs/2006.09287 (2020)
2010 – 2019
- 2019
- [j1]Daniele Ucci, Leonardo Aniello
, Roberto Baldoni:
Survey of machine learning techniques for malware analysis. Comput. Secur. 81: 123-147 (2019) - 2017
- [c6]Daniele Ucci
, Leonardo Aniello, Roberto Baldoni:
Share a pie?: Privacy-Preserving Knowledge Base Export through Count-min Sketches. CODASPY 2017: 95-106 - [c5]Luca Massarelli, Leonardo Aniello
, Claudio Ciccotelli, Leonardo Querzoni
, Daniele Ucci
, Roberto Baldoni:
Android malware family classification based on resource consumption over time. MALWARE 2017: 31-38 - [c4]Marco Angelini
, Leonardo Aniello, Simone Lenti
, Giuseppe Santucci, Daniele Ucci
:
The goods, the bads and the uglies: Supporting decisions in malware detection through visual analytics. VizSEC 2017: 1-8 - [i2]Luca Massarelli, Leonardo Aniello, Claudio Ciccotelli, Leonardo Querzoni, Daniele Ucci, Roberto Baldoni:
Android Malware Family Classification Based on Resource Consumption over Time. CoRR abs/1709.00875 (2017) - [i1]Daniele Ucci, Leonardo Aniello, Roberto Baldoni:
Survey on the Usage of Machine Learning Techniques for Malware Analysis. CoRR abs/1710.08189 (2017) - 2016
- [c3]Giuseppe Laurenza
, Daniele Ucci
, Leonardo Aniello, Roberto Baldoni:
An Architecture for Semi-Automatic Collaborative Malware Analysis for CIs. DSN Workshops 2016: 137-142 - [c2]Zigrid Shehu, Claudio Ciccotelli, Daniele Ucci
, Leonardo Aniello, Roberto Baldoni:
Towards the Usage of Invariant-Based App Behavioral Fingerprinting for the Detection of Obfuscated Versions of Known Malware. NGMAST 2016: 121-126 - 2014
- [c1]Roberto Baldoni, Fabrizio d'Amore
, Massimo Mecella
, Daniele Ucci
:
A Software Architecture for Progressive Scanning of On-line Communities. ICDCS Workshops 2014: 207-212
Coauthor Index
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